Securing a place in your customer's heart

In the highly competitive financial services industry, market insights, predictive factors and meaningful analyses – often trapped in mountains of data – bring advantage to companies that can successfully uncover and act on them. For Korea's Hyundai Securities Co., the use of SAS® Customer Intelligence to analyze customer segments and improve marketing performance has become central to its success.

Established in 1962, Hyundai Securities specializes in security brokerage, asset management and corporate finance, with Korea's largest branch network of 138 local offices and seven overseas branches. Aiming to become "the leading investment bank that provides the best financial solutions in Korea," Hyundai has sought to further position itself as a leader across the Asia Pacific region.

After implementing the system, we wanted to confirm its predictive accuracy, so we commissioned a research firm to conduct a phone survey and focus group interview. The results turned out to be very similar to what the SAS analysis predicted.

Seung-Gwon Park
Manager, Customer Marketing

One strategic initiative to pursue this vision was the implementation of SAS for more systematic customer analysis and predictive modeling.

Previously, the company had built and deployed an enterprise data warehouse. However, that effort withered because of a lack of appropriate and sufficient analytics tools to tap into the underlying value of that warehouse.

More recently, as the groundswell for customer analysis became stronger, Hyundai built its own customer analytic platform (CAP) that provided some rudimentary analyses on customer relationship marketing (CRM) – but it still lacked predictive modeling, segmentation and other functions that the company needed.

From pilot to enterprise

To take its CRM analytics efforts to a higher level, Hyundai integrated SAS with its CAP. The first phase was a monthlong, companywide pilot project to analyze new-customer retention rates. The pilot enabled all employees to test how they could use the SAS analytical capabilities by creating and issuing management reports across departments.

Based on the success of that pilot phase, Hyundai soon rolled out the solution to all of its branch offices to analyze a broader range of customer and marketing issues.

"We're now able to analyze areas such as new-customer acquisition channels, customer retention rates, customer profitability by management types, and customer preference analysis by areas," said Seung-Gwon Park, Customer Marketing Team Manager. "After implementing the system, we wanted to confirm its predictive accuracy, so we commissioned a research firm to conduct a phone survey and focus group interview. The results turned out to be very similar to what the SAS analysis predicted."

For example, SAS estimated that new customers brought in by salespersons to be about 10 percent. The commissioned survey of 1,000 customers found nearly identical results. This was also the case with customer preferences by areas and new-customer retention rates.

With verified accuracy of the SAS analyses, Hyundai now uses SAS for customer segmentation, which has driven important decisions in customer marketing and in other areas of the business.

Ramping up the offers

Hyundai also uses SAS to build and use "customer master segments" for marketing.

The company first selects highly related variables such as assets, profit and loss, contribution profit, and products from its customer database. Then it defines the final 11 basic segments through clustering. Based on the segments, the company generates customer information for each marketing channel by integrating with its sales force automation (SFA) system.

"We conducted a two-month test," said Park. "Our outbound sales calls to these targeted accounts received a much better response than before."

Hyundai is also applying SAS to design customer management programs such as a VIP service program and a new-customer welcome program.

Hyundai plans to gain further SAS analytics experience while focusing on applications for marketing and sales, such as customer acquisition and customer retention.

Based on the results and corresponding internal consensus, it will strengthen the predictive capabilities through even more precise modeling.

Specifically, Hyundai Securities plans to conduct a cross-selling campaign, based on its analysis of customer purchase patterns and moving routes. A product-suggestion matching model for customers, based on an analysis of their purchase preferences, will be a key to this system.

Challenge

Hyundai Securities had vast amounts of data sitting in an enterprise data warehouse. More valuable insight was needed from this data in order to improve outbound sales performance. More advanced customer segmentation, clustering and analytical techniques were needed to start making relevant offers to customers who have high propensities to purchase.

Solution

Benefits

Improved overall marketing performance by segmenting and clustering customers in order to predict and identify – with speed and accuracy – which customers will respond favorably to certain offers as well as to predict which customers are most likely to churn.

The results illustrated in this article are specific to the particular situations, business models, data input, and computing environments described herein. Each SAS customer’s experience is unique based on business and technical variables and all statements must be considered non-typical. Actual savings, results, and performance characteristics will vary depending on individual customer configurations and conditions. SAS does not guarantee or represent that every customer will achieve similar results. The only warranties for SAS products and services are those that are set forth in the express warranty statements in the written agreement for such products and services. Nothing herein should be construed as constituting an additional warranty. Customers have shared their successes with SAS as part of an agreed-upon contractual exchange or project success summarization following a successful implementation of SAS software. Brand and product names are trademarks of their respective companies.